Results 181 to 190 of about 993,426 (339)

Effect of perioperative oral management on the prevention of surgical site infection after colorectal cancer surgery: A multicenter retrospective analysis of 698 patients via analysis of covariance using propensity score. [PDF]

Medicine (Baltimore), 2018
Nobuhara H, Yanamoto S, Funahara M, Matsugu Y, Hayashida S, Soutome S, Kawakita A, Ikeda S, Itamoto T, Umeda M.   +9 more
europepmc   +1 more source

A simple sample size formula for analysis of covariance in cluster randomized trials

Statistics in Medicine, 2012
S. Teerenstra, S. Eldridge, M. Graff, Esther Hoop, G. Borm   +4 more
semanticscholar   +1 more source

Validation of a model for continued employment for general workers with mental illness: A covariance analysis based on evidence from Japan [PDF]

Yoshitomo Fukuura, Yukako Shigematsu, Yumi Mizuochi   +2 more
openalex   +1 more source

Data Analysis Using Experimental Design Model Factorial Analysis of Variance/Covariance (DMAOVC.BAS)

, 2021
Wesley E. Newton
openalex   +1 more source

Feature Selection for Machine Learning‐Driven Accelerated Discovery and Optimization in Emerging Photovoltaics: A Review

Advanced Intelligent Discovery, EarlyView.
Feature selection combined with machine learning and high‐throughput experimentation enables efficient handling of high‐dimensional datasets in emerging photovoltaics. This approach accelerates material discovery, improves process optimization, and strengthens stability prediction, while overcoming challenges in data quality and model scalability to ...
Jiyun Zhang, Jiayi Tan, Qizhen Song, Tian Du, Jens Hauch, Christoph J. Brabec   +5 more
wiley   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

COVID-19 and lockdown in India: Evaluation using analysis of covariance

, 2020
Tak A, Das B, Gahlot S.
europepmc   +1 more source

Spectral Efficiency Analysis of Cell-free Distributed Massive MIMO Systems with Imperfect Covariance Matrix

, 2021
Feng Ye, Jiamin Li, Pengcheng Zhu, Dongming Wang, Xiaohu You   +4 more
openalex   +1 more source

Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

Advanced Intelligent Discovery, EarlyView.
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour, Sara Soltanabadi Farshi, Tuanna Ozcan, Amir Mohammad Ketabchi, Alper Kiraz, Savas Tasoglu   +5 more
wiley   +1 more source

Performance Analysis of Tyler's Covariance Estimator [PDF]

, 2014
Ilya Soloveychik, Ami Wiesel
openalex   +1 more source